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<div class="title">NEDirectConvolution3x3.h</div>  </div>
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<a href="_n_e_direct_convolution3x3_8h.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Copyright (c) 2017-2018 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> * of this software and associated documentation files (the &quot;Software&quot;), to</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment"> * deal in the Software without restriction, including without limitation the</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> * furnished to do so, subject to the following conditions:</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;</div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;<span class="preprocessor">#ifndef __ARM_COMPUTE_NECONVOLUTIONKERNEL3x3_H__</span></div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;<span class="preprocessor">#define __ARM_COMPUTE_NECONVOLUTIONKERNEL3x3_H__</span></div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;</div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;<span class="preprocessor">#include &lt;arm_neon.h&gt;</span></div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;</div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;{</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;<span class="keyword">namespace </span>detail</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;{</div><div class="line"><a name="l00034"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1detail.xhtml#afaba543670e99c2483e0bd1996201ba3">   34</a></span>&#160;<span class="keyword">inline</span> float32x4x3_t <a class="code" href="namespacearm__compute_1_1detail.xhtml#afaba543670e99c2483e0bd1996201ba3">load_matrix_row</a>(<span class="keyword">const</span> <span class="keywordtype">float</span> *ptr)</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;{</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;    <span class="keyword">const</span> float32x4x3_t r =</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;    {</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;        {</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;            vld1q_dup_f32(ptr),</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;            vld1q_dup_f32(1 + ptr),</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;            vld1q_dup_f32(2 + ptr)</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;        }</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;    };</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;    <span class="keywordflow">return</span> r;</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;}</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> str<span class="keywordtype">id</span>ex&gt;</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;float32x4x2_t <a class="code" href="namespacearm__compute_1_1detail.xhtml#ac064ba58efa26ec2599bc8f50d3e0851">convolve_3x3</a>(<span class="keyword">const</span> <span class="keywordtype">float</span> *in_top, <span class="keyword">const</span> <span class="keywordtype">float</span> *in_mid, <span class="keyword">const</span> <span class="keywordtype">float</span> *in_low, <span class="keyword">const</span> float32x4x3_t &amp;m0, <span class="keyword">const</span> float32x4x3_t &amp;m1, <span class="keyword">const</span> float32x4x3_t &amp;m2, <span class="keywordtype">int</span> fixed_point_position);</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;<span class="keyword">template</span> &lt;&gt;</div><div class="line"><a name="l00051"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1detail.xhtml#a60ec1bb53624bf71d2b0bd885e3234d7">   51</a></span>&#160;<span class="keyword">inline</span> float32x4x2_t <a class="code" href="namespacearm__compute_1_1detail.xhtml#a60ec1bb53624bf71d2b0bd885e3234d7">convolve_3x3&lt;1&gt;</a>(<span class="keyword">const</span> <span class="keywordtype">float</span> *in_top, <span class="keyword">const</span> <span class="keywordtype">float</span> *in_mid, <span class="keyword">const</span> <span class="keywordtype">float</span> *in_low, <span class="keyword">const</span> float32x4x3_t &amp;m0, <span class="keyword">const</span> float32x4x3_t &amp;m1, <span class="keyword">const</span> float32x4x3_t &amp;m2, <span class="keywordtype">int</span> fixed_point_position)</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;{</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;    <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(fixed_point_position);</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;    <span class="keyword">const</span> float32x4x3_t vtop =</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;    {</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;        {</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;            vld1q_f32(in_top),</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;            vld1q_f32(in_top + 4),</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;            vld1q_f32(in_top + 8)</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;        }</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;    };</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;    <span class="keyword">const</span> float32x4x3_t vmid =</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    {</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;        {</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;            vld1q_f32(in_mid),</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;            vld1q_f32(in_mid + 4),</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;            vld1q_f32(in_mid + 8)</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;        }</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;    };</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;    <span class="keyword">const</span> float32x4x3_t vlow =</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;    {</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;        {</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;            vld1q_f32(in_low),</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;            vld1q_f32(in_low + 4),</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;            vld1q_f32(in_low + 8)</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;        }</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;    };</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;    float32x4x2_t out =</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;    {</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;        {</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;            vmulq_f32(vtop.val[0], m0.val[0]),</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;            vmulq_f32(vtop.val[1], m0.val[0])</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;        }</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;    };</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;    out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vtop.val[0], vtop.val[1], 1), m0.val[1]);</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;    out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vtop.val[0], vtop.val[1], 2), m0.val[2]);</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;    out.val[0] = vmlaq_f32(out.val[0], vmid.val[0], m1.val[0]);</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;    out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vmid.val[0], vmid.val[1], 1), m1.val[1]);</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;    out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vmid.val[0], vmid.val[1], 2), m1.val[2]);</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;    out.val[0] = vmlaq_f32(out.val[0], vlow.val[0], m2.val[0]);</div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;    out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vlow.val[0], vlow.val[1], 1), m2.val[1]);</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;    out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vlow.val[0], vlow.val[1], 2), m2.val[2]);</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;    out.val[1] = vmlaq_f32(out.val[1], vextq_f32(vtop.val[1], vtop.val[2], 1), m0.val[1]);</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;    out.val[1] = vmlaq_f32(out.val[1], vextq_f32(vtop.val[1], vtop.val[2], 2), m0.val[2]);</div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;</div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;    out.val[1] = vmlaq_f32(out.val[1], vmid.val[1], m1.val[0]);</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;    out.val[1] = vmlaq_f32(out.val[1], vextq_f32(vmid.val[1], vmid.val[2], 1), m1.val[1]);</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;    out.val[1] = vmlaq_f32(out.val[1], vextq_f32(vmid.val[1], vmid.val[2], 2), m1.val[2]);</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;    out.val[1] = vmlaq_f32(out.val[1], vlow.val[1], m2.val[0]);</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;    out.val[1] = vmlaq_f32(out.val[1], vextq_f32(vlow.val[1], vlow.val[2], 1), m2.val[1]);</div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;    out.val[1] = vmlaq_f32(out.val[1], vextq_f32(vlow.val[1], vlow.val[2], 2), m2.val[2]);</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;    <span class="keywordflow">return</span> out;</div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;}</div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;<span class="keyword">template</span> &lt;&gt;</div><div class="line"><a name="l00111"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1detail.xhtml#ac5a80612d739ca7ab7db7e26c05796e1">  111</a></span>&#160;<span class="keyword">inline</span> float32x4x2_t <a class="code" href="namespacearm__compute_1_1detail.xhtml#ac5a80612d739ca7ab7db7e26c05796e1">convolve_3x3&lt;2&gt;</a>(<span class="keyword">const</span> <span class="keywordtype">float</span> *in_top, <span class="keyword">const</span> <span class="keywordtype">float</span> *in_mid, <span class="keyword">const</span> <span class="keywordtype">float</span> *in_low, <span class="keyword">const</span> float32x4x3_t &amp;m0, <span class="keyword">const</span> float32x4x3_t &amp;m1, <span class="keyword">const</span> float32x4x3_t &amp;m2, <span class="keywordtype">int</span> fixed_point_position)</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;{</div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;    float32x4x2_t out = <a class="code" href="namespacearm__compute_1_1detail.xhtml#a60ec1bb53624bf71d2b0bd885e3234d7">convolve_3x3&lt;1&gt;</a>(in_top, in_mid, in_low, m0, m1, m2, fixed_point_position);</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;    out.val[0]        = vsetq_lane_f32(vgetq_lane_f32(out.val[0], 2), out.val[0], 1);</div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;    out.val[0]        = vsetq_lane_f32(vgetq_lane_f32(out.val[1], 0), out.val[0], 2);</div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;    out.val[0]        = vsetq_lane_f32(vgetq_lane_f32(out.val[1], 2), out.val[0], 3);</div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;    <span class="keywordflow">return</span> out;</div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;}</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;</div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;<span class="keyword">template</span> &lt;&gt;</div><div class="line"><a name="l00121"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1detail.xhtml#adb5abdd9cafbff3bdfc6a5a9ec6bbe5c">  121</a></span>&#160;<span class="keyword">inline</span> float32x4x2_t <a class="code" href="namespacearm__compute_1_1detail.xhtml#adb5abdd9cafbff3bdfc6a5a9ec6bbe5c">convolve_3x3&lt;3&gt;</a>(<span class="keyword">const</span> <span class="keywordtype">float</span> *in_top, <span class="keyword">const</span> <span class="keywordtype">float</span> *in_mid, <span class="keyword">const</span> <span class="keywordtype">float</span> *in_low, <span class="keyword">const</span> float32x4x3_t &amp;m0, <span class="keyword">const</span> float32x4x3_t &amp;m1, <span class="keyword">const</span> float32x4x3_t &amp;m2, <span class="keywordtype">int</span> fixed_point_position)</div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;{</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;    float32x4x2_t out = <a class="code" href="namespacearm__compute_1_1detail.xhtml#a60ec1bb53624bf71d2b0bd885e3234d7">convolve_3x3&lt;1&gt;</a>(in_top, in_mid, in_low, m0, m1, m2, fixed_point_position);</div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;    out.val[0]        = vsetq_lane_f32(vgetq_lane_f32(out.val[0], 3), out.val[0], 1);</div><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;    <span class="keywordflow">return</span> out;</div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;}</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> str<span class="keywordtype">id</span>ex&gt;</div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1detail.xhtml#a1ac67082e6f68cb7ed1939240fb6bdb5">store_results</a>(<span class="keywordtype">float</span> *buffer, <span class="keyword">const</span> float32x4x2_t &amp;values);</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;<span class="keyword">template</span> &lt;&gt;</div><div class="line"><a name="l00132"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1detail.xhtml#ad61a01ef06cc3c41e4bb5006d9307687">  132</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1detail.xhtml#ad61a01ef06cc3c41e4bb5006d9307687">store_results&lt;1&gt;</a>(<span class="keywordtype">float</span> *buffer, <span class="keyword">const</span> float32x4x2_t &amp;values)</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;{</div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;    vst1q_f32(buffer, values.val[0]);</div><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;    vst1q_f32(buffer + 4, values.val[1]);</div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;}</div><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;<span class="keyword">template</span> &lt;&gt;</div><div class="line"><a name="l00139"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1detail.xhtml#abaf3037739c190361ad3f827d73440a1">  139</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1detail.xhtml#abaf3037739c190361ad3f827d73440a1">store_results&lt;2&gt;</a>(<span class="keywordtype">float</span> *buffer, <span class="keyword">const</span> float32x4x2_t &amp;values)</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;{</div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;    vst1q_f32(buffer, values.val[0]);</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;}</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;<span class="keyword">template</span> &lt;&gt;</div><div class="line"><a name="l00145"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1detail.xhtml#a208468ac4ffbfe19d7fb03402ca927f6">  145</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1detail.xhtml#a208468ac4ffbfe19d7fb03402ca927f6">store_results&lt;3&gt;</a>(<span class="keywordtype">float</span> *buffer, <span class="keyword">const</span> float32x4x2_t &amp;values)</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;{</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;    vst1_f32(buffer, vget_low_f32(values.val[0]));</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;}</div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;</div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> str<span class="keywordtype">id</span>ex&gt;</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;<span class="keywordtype">int</span> <a class="code" href="namespacearm__compute_1_1detail.xhtml#a30f6368deaea5f10f9dd1bbaa28c24e6">get_input_num_elems_processed</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_elems_written_per_iteration);</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;</div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;<span class="keyword">template</span> &lt;&gt;</div><div class="line"><a name="l00154"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1detail.xhtml#a7a08a003e6ce7ea86cb7d8f4523c0eb5">  154</a></span>&#160;<span class="keywordtype">int</span> <a class="code" href="namespacearm__compute_1_1detail.xhtml#a7a08a003e6ce7ea86cb7d8f4523c0eb5">get_input_num_elems_processed&lt;1&gt;</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_elems_written_per_iteration)</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;{</div><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;    <span class="keywordflow">return</span> num_elems_written_per_iteration;</div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;}</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;<span class="keyword">template</span> &lt;&gt;</div><div class="line"><a name="l00160"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1detail.xhtml#adbdb2272e2409d0c249ba467eaac81ea">  160</a></span>&#160;<span class="keywordtype">int</span> <a class="code" href="namespacearm__compute_1_1detail.xhtml#adbdb2272e2409d0c249ba467eaac81ea">get_input_num_elems_processed&lt;2&gt;</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_elems_written_per_iteration)</div><div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;{</div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;    <span class="keywordflow">return</span> num_elems_written_per_iteration &lt;&lt; 1;</div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;}</div><div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;</div><div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;<span class="keyword">template</span> &lt;&gt;</div><div class="line"><a name="l00166"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1detail.xhtml#ae2a6fee9c18f26a5fab56c2d14289705">  166</a></span>&#160;<span class="keywordtype">int</span> <a class="code" href="namespacearm__compute_1_1detail.xhtml#ae2a6fee9c18f26a5fab56c2d14289705">get_input_num_elems_processed&lt;3&gt;</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_elems_written_per_iteration)</div><div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;{</div><div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;    <span class="keywordflow">return</span> num_elems_written_per_iteration * 3;</div><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;}</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;}</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;} <span class="comment">// namespace arm_compute</span></div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* __ARM_COMPUTE_NECONVOLUTIONKERNEL3x3_H__ */</span><span class="preprocessor"></span></div><div class="ttc" id="namespacearm__compute_1_1detail_xhtml_ac5a80612d739ca7ab7db7e26c05796e1"><div class="ttname"><a href="namespacearm__compute_1_1detail.xhtml#ac5a80612d739ca7ab7db7e26c05796e1">arm_compute::detail::convolve_3x3&lt; 2 &gt;</a></div><div class="ttdeci">float32x4x2_t convolve_3x3&lt; 2 &gt;(const float *in_top, const float *in_mid, const float *in_low, const float32x4x3_t &amp;m0, const float32x4x3_t &amp;m1, const float32x4x3_t &amp;m2, int fixed_point_position)</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_direct_convolution3x3_8h_source.xhtml#l00111">NEDirectConvolution3x3.h:111</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1detail_xhtml_a60ec1bb53624bf71d2b0bd885e3234d7"><div class="ttname"><a href="namespacearm__compute_1_1detail.xhtml#a60ec1bb53624bf71d2b0bd885e3234d7">arm_compute::detail::convolve_3x3&lt; 1 &gt;</a></div><div class="ttdeci">float32x4x2_t convolve_3x3&lt; 1 &gt;(const float *in_top, const float *in_mid, const float *in_low, const float32x4x3_t &amp;m0, const float32x4x3_t &amp;m1, const float32x4x3_t &amp;m2, int fixed_point_position)</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_direct_convolution3x3_8h_source.xhtml#l00051">NEDirectConvolution3x3.h:51</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1detail_xhtml_ae2a6fee9c18f26a5fab56c2d14289705"><div class="ttname"><a href="namespacearm__compute_1_1detail.xhtml#ae2a6fee9c18f26a5fab56c2d14289705">arm_compute::detail::get_input_num_elems_processed&lt; 3 &gt;</a></div><div class="ttdeci">int get_input_num_elems_processed&lt; 3 &gt;(unsigned int num_elems_written_per_iteration)</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_direct_convolution3x3_8h_source.xhtml#l00166">NEDirectConvolution3x3.h:166</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">This file contains all available output stages for GEMMLowp on OpenCL. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00001">00_introduction.dox:1</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1detail_xhtml_adbdb2272e2409d0c249ba467eaac81ea"><div class="ttname"><a href="namespacearm__compute_1_1detail.xhtml#adbdb2272e2409d0c249ba467eaac81ea">arm_compute::detail::get_input_num_elems_processed&lt; 2 &gt;</a></div><div class="ttdeci">int get_input_num_elems_processed&lt; 2 &gt;(unsigned int num_elems_written_per_iteration)</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_direct_convolution3x3_8h_source.xhtml#l00160">NEDirectConvolution3x3.h:160</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a6dc630a6ae9cc063b3924bcea8dee9d6"><div class="ttname"><a href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a></div><div class="ttdeci">#define ARM_COMPUTE_UNUSED(...)</div><div class="ttdoc">To avoid unused variables warnings. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00159">Error.h:159</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1detail_xhtml_a1ac67082e6f68cb7ed1939240fb6bdb5"><div class="ttname"><a href="namespacearm__compute_1_1detail.xhtml#a1ac67082e6f68cb7ed1939240fb6bdb5">arm_compute::detail::store_results</a></div><div class="ttdeci">void store_results(float *buffer, const float32x4x2_t &amp;values)</div><div class="ttdoc">Stores a float32x4x2_t array into a memory location. </div></div>
<div class="ttc" id="namespacearm__compute_1_1detail_xhtml_adb5abdd9cafbff3bdfc6a5a9ec6bbe5c"><div class="ttname"><a href="namespacearm__compute_1_1detail.xhtml#adb5abdd9cafbff3bdfc6a5a9ec6bbe5c">arm_compute::detail::convolve_3x3&lt; 3 &gt;</a></div><div class="ttdeci">float32x4x2_t convolve_3x3&lt; 3 &gt;(const float *in_top, const float *in_mid, const float *in_low, const float32x4x3_t &amp;m0, const float32x4x3_t &amp;m1, const float32x4x3_t &amp;m2, int fixed_point_position)</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_direct_convolution3x3_8h_source.xhtml#l00121">NEDirectConvolution3x3.h:121</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1detail_xhtml_a208468ac4ffbfe19d7fb03402ca927f6"><div class="ttname"><a href="namespacearm__compute_1_1detail.xhtml#a208468ac4ffbfe19d7fb03402ca927f6">arm_compute::detail::store_results&lt; 3 &gt;</a></div><div class="ttdeci">void store_results&lt; 3 &gt;(float *buffer, const float32x4x2_t &amp;values)</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_direct_convolution3x3_8h_source.xhtml#l00145">NEDirectConvolution3x3.h:145</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1detail_xhtml_ac064ba58efa26ec2599bc8f50d3e0851"><div class="ttname"><a href="namespacearm__compute_1_1detail.xhtml#ac064ba58efa26ec2599bc8f50d3e0851">arm_compute::detail::convolve_3x3</a></div><div class="ttdeci">float32x4x2_t convolve_3x3(const float *in_top, const float *in_mid, const float *in_low, const float32x4x3_t &amp;m0, const float32x4x3_t &amp;m1, const float32x4x3_t &amp;m2, int fixed_point_position)</div></div>
<div class="ttc" id="namespacearm__compute_1_1detail_xhtml_ad61a01ef06cc3c41e4bb5006d9307687"><div class="ttname"><a href="namespacearm__compute_1_1detail.xhtml#ad61a01ef06cc3c41e4bb5006d9307687">arm_compute::detail::store_results&lt; 1 &gt;</a></div><div class="ttdeci">void store_results&lt; 1 &gt;(float *buffer, const float32x4x2_t &amp;values)</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_direct_convolution3x3_8h_source.xhtml#l00132">NEDirectConvolution3x3.h:132</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1detail_xhtml_afaba543670e99c2483e0bd1996201ba3"><div class="ttname"><a href="namespacearm__compute_1_1detail.xhtml#afaba543670e99c2483e0bd1996201ba3">arm_compute::detail::load_matrix_row</a></div><div class="ttdeci">float32x4x3_t load_matrix_row(const float *ptr)</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_direct_convolution3x3_8h_source.xhtml#l00034">NEDirectConvolution3x3.h:34</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1detail_xhtml_a30f6368deaea5f10f9dd1bbaa28c24e6"><div class="ttname"><a href="namespacearm__compute_1_1detail.xhtml#a30f6368deaea5f10f9dd1bbaa28c24e6">arm_compute::detail::get_input_num_elems_processed</a></div><div class="ttdeci">int get_input_num_elems_processed(unsigned int num_elems_written_per_iteration)</div><div class="ttdoc">Get the number of elements processed on 3x3 convolution. </div></div>
<div class="ttc" id="namespacearm__compute_1_1detail_xhtml_a7a08a003e6ce7ea86cb7d8f4523c0eb5"><div class="ttname"><a href="namespacearm__compute_1_1detail.xhtml#a7a08a003e6ce7ea86cb7d8f4523c0eb5">arm_compute::detail::get_input_num_elems_processed&lt; 1 &gt;</a></div><div class="ttdeci">int get_input_num_elems_processed&lt; 1 &gt;(unsigned int num_elems_written_per_iteration)</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_direct_convolution3x3_8h_source.xhtml#l00154">NEDirectConvolution3x3.h:154</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1detail_xhtml_abaf3037739c190361ad3f827d73440a1"><div class="ttname"><a href="namespacearm__compute_1_1detail.xhtml#abaf3037739c190361ad3f827d73440a1">arm_compute::detail::store_results&lt; 2 &gt;</a></div><div class="ttdeci">void store_results&lt; 2 &gt;(float *buffer, const float32x4x2_t &amp;values)</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_direct_convolution3x3_8h_source.xhtml#l00139">NEDirectConvolution3x3.h:139</a></div></div>
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